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Abstract Background Pseudomonas syringae pv. tagetis (Pstag) causes apical chlorosis on sunflower and various other plants of the Asteraceae family. Whole genome sequencing of Pstag strain EB037 and transposon-mutant derivatives, no longer capable of causing apical chlorosis, was conducted to improve understanding of the molecular basis of disease caused by this pathogen. Results A tripartite pathogenicity island (TPI) for a Type III secretion system (T3SS) with the complete hrp-hrc gene cluster and conserved effector locus was detected in the Pstag genome. The exchange effector region of the TPI contained genes potentially functioning in detoxification of the environment as well as two integrases, but no previously described T3SS effector homologues. In all, the Pstag EB037 genome contained homologues for at least 44 T3SS effectors with 30 having known functions. Plasmids similar with pTagA and pTagB of P. syringae pv. tagetis ICMP 4091 were also identified in the Pstag genome. The pTagA-like plasmid contained a complete Type IV secretion system (T4SS) with associated putative killer protein. Mutational analysis using transposon insertions within genes functioning in the T3SS and T4SS confirmed the role of both secretion systems and these plasmids in apical chlorosis. Transposon mutagenesis identified an additional 22 genes in loci, including two more plasmid-bound loci, involved in apical chlorosis on sunflower; some with known importance in other plant or animal pathosystems. Conclusions Apical chlorosis disease caused by Pstag EB037 is the result of a complex set of mechanisms. This study identified a TPI and homologues for at least 44 T3SS effectors, 30 of which with known functions in disease, and another 20 genes in loci correlated with apical chlorosis on sunflower. Two plasmids were detected that were correlated with apical chlorosis disease, one of which contained a complete T4SS that was correlated with disease. To our knowledge, we provide the first direct evidence for a T4SS functioning in disease by a pathogenic P. syringae strain.

This article considers the value of honors education beyond its marked contributions to enrollment management goals. Suggesting that quantitative assessments toward understanding the value of honors fail to capture its breadth, interdisciplinary focus, and engagement, authors posit a new way of measuring impacts from "contagion model" (spillover to campus and beyond) to "permeability model" (interface across campus). Pointing to the benefits of permeability for both honors and the broader campus communities, authors encourage practitioners to foster exchange in curricular offerings, spatial inputs, scholarly outputs, extramural funding, and institutional support. The meaning and history of organizational permeability is explored, and examples are provided.

Abstract Large-scale folding of sedimentary rock is generally considered to be a response to horizontal tectonic shortening. We test an alternative hypothesis where we propose that in basins with high sedimentation rates where folds are cored by mechanically weak mobile shale, fold growth can be amplified by the gravitational loading of the weak underlying shale. We use two-dimensional plane-strain, finite element code to investigate the mechanics of growth of a shale-cored fold in the South Caspian Sea Basin, where c.10 km of sediment was deposited in the last 6 My. The overburden and syn-kinematic sediments are modelled as poro-elastoplastic materials using a modified Cam-Clay critical state model and the mobile shale is modelled as visco-plastic Herschell-Bulkley material, representative of conditions at critical state. The results show that the atypical geometries of the fold strata can be explained by the application of horizontal shortening and simultaneous sediment loading of the visco-plastic layer. The viscosity of the shale determines whether differential loading will cause fold growth and its density controls the magnitude of fold amplification, with a lower density causing greater fold amplification. Results demonstrate that the magnitude of shale inflation is controlled by complex interaction of the relative amounts of shortening and sedimentation rate.

Abstract CRISPR‐Cas12a works like a sophisticated algorithm in nucleic acid detection, yet its challenge lies in sometimes failing to distinguish targets with mismatches due to its specificity limitations. Here, the mismatch profiles, including the quantity, location, and type of mismatches in the CRISPR‐Cas12a reaction, are investigated and its various tolerances to mismatches are discovered. By harnessing the specificity defect of the CRISPR‐Cas12a enzyme, a dual‐mode detection strategy is designed, which includes approximate matching and precise querying of target sequences and develop a programmable multiplexed nucleic acid assay. With the assay, 14 high‐risk human papillomavirus (HPV) subtypes are simultaneously detected, collectively responsible for 99% of cervical cancer cases, with attomolar sensitivity. Specifically, the assay not only distinguishes HPV16 and HPV18, the two most common subtypes but also detects 12 other high‐risk pooled HPV subtypes. To enable low‐cost point‐of‐care testing, the assay is incorporated into a paper‐based microfluidic chip. Furthermore, the clinical performance of the paper‐based microfluidic chip is validated by testing 75 clinical swab samples, achieving performance comparable to that of PCR. This programmable multiplexed nucleic acid assay has the potential to be widely applied for sensitive, specific, and simultaneous detection of different pathogens.

Hepatocellular carcinoma (HCC) is among the most common cancers worldwide, and tumor recurrence following liver resection or transplantation is one of the highest contributors to mortality in HCC patients after surgery. Using artificial intelligence (AI), we developed an interdisciplinary model to predict HCC recurrence and patient survival following surgery. We collected whole-slide H&E images, clinical variables, and follow-up data from 300 patients with HCC who underwent transplant and 169 patients who underwent resection at the Cleveland Clinic. A deep learning model was trained to predict recurrence-free survival (RFS) and disease-specific survival (DSS) from the H&E-stained slides. Repeated cross-validation splits were used to compute robust C-index estimates, and the results were compared to those obtained by fitting a Cox proportional hazard model using only clinical variables. While the deep learning model alone was predictive of recurrence and survival among patients in both cohorts, integrating the clinical and histologic models significantly increased the C-index in each cohort. In every subgroup analyzed, we found that a combined clinical and deep learning model better predicted post-surgical outcome in HCC patients compared to either approach independently.

Callose, a β-(1,3)-d-glucan polymer, is essential for regulating intercellular trafficking via plasmodesmata (PD). Pathogens manipulate PD-localized proteins to enable intercellular trafficking by removing callose at PD or, conversely, by increasing callose accumulation at PD to limit intercellular trafficking during infection. Plant defense hormones like salicylic acid regulate PD-localized proteins to control PD and intercellular trafficking during immune defense responses such as systemic acquired resistance. Measuring callose deposition at PD in plants has therefore emerged as a popular parameter for assessing likely intercellular trafficking activity during plant immunity. Despite the popularity of this metric, there is no standard for how these measurements should be made. In this study, three commonly used methods for identifying and quantifying plasmodesmal callose by aniline blue staining were evaluated to determine the most effective in the Nicotiana benthamiana leaf model. The results reveal that the most reliable method used aniline blue staining and fluorescence microscopy to measure callose deposition in fixed tissue. Manual or semiautomated workflows for image analysis were also compared and found to produce similar results, although the semiautomated workflow produced a wider distribution of data points. [Graphic: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Certain Trichoderma isolates provide biofertilizer, biocontrol, and other plant-beneficial activities while inhabiting the soil or internal plant tissue, and their use in agricultural systems can contribute to sustainable food production. It is thought that colonization of soil or internal plant tissue is fundamental for biocontrol and biofertilizer applications. Our collective analyses of prior surveys, where the tef1α sequence was almost exclusively used to identify Trichoderma species, showed that isolates from the Harzianum complex clade, the T. asperellum/T. asperelloides group, T. virens, T. hamatum, and T. atroviride were prevalent in soil and/or as endophytes. Population structure and genetic diversity based on the genetic markers tef1α, rpb2, and ITS were investigated, and new lineages with statistical bootstrap support within T. atroviride, T. asperellum, T. hamatum, and T. virens populations were found. The nearest relatives of some of these species were also revealed. Choosing isolates from among more than 500 known Trichoderma species for use in non-targeted evaluation screens for biocontrol or biofertilizer applications is time-consuming and expensive. Preferentially selecting isolates from T. atroviride, T. asperellum/T. asperelloides, T. hamatum, the T. harzianum complex clade, T. virens, and possibly nearest relatives may speed the identification of candidates for commercialization due to the demonstrated ability of these species to successfully inhabit the soil and internal plant tissue. To our knowledge, this is the first report where dominant soil and endophytic Trichoderma species were identified from past survey data and population structure and genetic diversity analyses conducted.

Cancer patients undergoing treatment with systemic cancer chemotherapy drugs often experience debilitating fatigue similar to sickness behavior, a normal response to infection or tissue damage caused by the production of the inflammatory cytokines IL-1beta, TNF-alpha, and IL-6. The p38 mitogen activated protein kinase (p38 MAPK) plays a central role in the production of these cytokines and consequently the development of sickness behavior. Targeted inhibitors of p38 MAPK can reduce systemic inflammatory cytokine production and the development of sickness behavior. Several systemic cancer chemotherapy drugs have been shown to stimulate inflammatory cytokine production, yet whether this response is related to a common ability to activate p38 MAPK is not known and is the focus of this study. This understanding may present the possibility of using p38 MAPK inhibitors to reduce chemotherapy-induced inflammatory cytokine production and consequently treatment-related fatigue. One caveat of this approach is a potential reduction in chemotherapeutic efficacy as some believe that p38 MAPK activity is required for chemotherapy-induced cytotoxicity of tumor cells. The purpose of this study was to demonstrate proof of principal that p38 MAPK inhibition can block chemotherapy-induced inflammatory cytokine production without inhibiting drug-induced cytotoxicity using murine peritoneal macrophages and Lewis Lung Carcinoma (LLC1) cells as model cell systems. Using these cells we assessed the requirement of etoposide, doxorubicin, 5-fluorouracil, and docetaxel for p38 MAPK in inflammatory cytokine production and cytotoxicity. Study findings demonstrate that clinically relevant doses of etoposide, doxorubicin, and 5-FU activated p38 MAPK in both macrophages and LLC1 cells. In contrast, docetaxel failed to activate p38 MAPK in either cell type. Activation of p38 MAPK mediated the drug's effects on inflammatory cytokine production in macrophages but not LLC1 cytotoxicity and this was confirmed with inhibitor studies.

Abstract Psilocybin and lysergic acid diethylamide (LSD) experiences can range from very positive to highly challenging (e.g., fear, grief, and paranoia). These challenging experiences contribute to hesitancy toward psychedelic-assisted psychotherapy among health care providers and patients. Co-use of 3,4-Methylenedioxy methamphetamine (MDMA) with psilocybin/LSD anecdotally reduces challenging experiences and enhances positive experiences associated with psilocybin/LSD. However, limited research has investigated the acute effects of co-use of MDMA and psilocybin/LSD. In a prospective convenience sample (N = 698) of individuals with plans to use psilocybin/LSD, we examined whether co-use of MDMA with psilocybin/LSD (n = 27) is associated with differences in challenging or positive experiences. Challenging experiences were measured using the Challenging Experiences Questionnaire and positive experiences were measured using the Mystical Experience Questionnaire and single-item measures of self-compassion, compassion, love, and gratitude. Potentially confounding variables were identified and included as covariates. Relative to psilocybin/LSD alone, co-use of psilocybin/LSD with a self-reported low (but not medium–high) dose of MDMA was associated with significantly less intense total challenging experiences, grief, and fear, as well as increased self-compassion, love and gratitude. Co-use of psilocybin/LSD and MDMA was not associated with differences in mystical-type experiences or compassion. Findings suggest co-use of MDMA with psilocybin/LSD may buffer against some aspects of challenging experiences and enhance certain positive experiences. Limitations include use of a convenience sample, small sample size, and non-experimental design. Additional studies (including controlled dose–response studies) that examine the effects and safety of co-administering MDMA with psilocybin/LSD (in healthy controls and clinical samples) are warranted and may assist the development of personalized treatments.

Abstract Ethanol extract of cell mass of Serratia marcescens strain N4-5, when applied as a treatment to cucumber seed, has been shown to provide control of the oomycete soil-borne plant pathogen Pythium ultimum equivalent to that provided by a seed-treatment chemical pesticide in some soils. Two dominant compounds in this extract, prodigiosin and the serratamolide serrawetin W1, were identified based on mass and collision induced dissociation mass fragmentation spectra. An additional four compounds with M+H+ masses (487, 541, 543, and 571) consistent with serratamolides reported in the literature were also detected. Several other compounds with M+H+ masses of 488, 536, 684, 834, 906, and 908 m/z were detected in this ethanol extract inconsistently over multiple liquid chromatography coupled with tandem mass spectrometry (LC/MS–MS) runs. A purified preparation of prodigiosin provided control of damping-off of cucumber caused by P. ultimum when applied as a seed treatment while ethanol extract of cell mass of strain Tn246, a transposon-mutant-derivative of strain N4-5, did not. Strain Tn246 contained a mini-Tn5 Km insertion in a prodigiosin biosynthetic gene and was deficient in production of prodigiosin. All other compounds detected in N4-5 extract were detected in the Tn246 extract. This is the first report demonstrating that prodigiosin can control a plant disease. Other compounds in ethanol extract of strain N4-5 may contribute to disease control.

Achieving global food security requires better use of natural, genetic, and importantly, human resources—knowledge. Technology must be created, and existing and new technology and knowledge deployed, and adopted by farmers and others engaged in agriculture. This requires collaboration amongst many professional communities world-wide including farmers, agribusinesses, policymakers, and multi-disciplinary scientific groups. Each community having its own knowledge-associated terminology, techniques, and types of data, collectively forms a barrier to collaboration. Knowledge management (KM) approaches are being implemented to capture knowledge from all communities and make it interoperable and accessible as a “group memory” to create a multi-professional, multidisciplinary knowledge economy. As an example, we present KM efforts at the US Department of Agriculture. Information and Communications Technology (ICT) is being developed to capture tacit and explicit knowledge assets including Big Data and transform it into curated knowledge products available, with permissions, to the agricultural community. Communities of Practice (CoP) of scientists, farmers, and others are being developed at USDA and elsewhere to foster knowledge exchange. Marrying CoPs to ICT-leveraged aspects of KM will speed development and adoption of needed agricultural solutions. Ultimately needed is a network of KM networks so that knowledge stored anywhere can be used globally in real time.

Gray bulb rot of tulips and bulbous iris is caused by the soil-borne fungal pathogen, Rhizoctonia tuliparum (Rtul). Sclerotia present in infected bulbs, as well as overwintering sclerotia in soil and field debris, are the primary sources of infection. A method for accurate and sensitive detection of Rtul from soil and infected bulbs, and estimation of inoculum threshold levels, is needed for the management of disease caused by this pathogen. We designed a unique set of primers targeting the ITS2 region of the Rtul genome and developed a highly sensitive quantitative PCR (qPCR)-based method for Rtul identification using these primers, where the threshold of detection was approximately 1 fg Rtul DNA. The assay was more sensitive with sclerotia collected from the field (natural) than with those grown in the lab, and more sensitive with natural-light than natural-dark sclerotia. Also, the detection method was more sensitive when sclerotia were extracted from soil than from bulb tissue. The qPCR method was highly specific, as no PCR amplification was detected when genomic DNA from 62 non-Rtul Rhizoctonia isolates from a wide range of anastomosis groups were tested. To understand the evolutionary relationships and genomic diversity of Rtul, we performed phylogenetics of the ITS1-5.8S-ITS2 region and ITS2-molecular morphometric characterization (MMC) of Rtul isolates. The three Rtul isolates whose ITS sequences were available in GenBank formed a distinct phylogenetic clade with Ceratobasidium anceps as the nearest relative. Furthermore, MMC analysis revealed genetic divergence among these three Rtul isolates.

Foliar diseases of maize cause severe economic losses in India and around the world. The increasing severity of maize leaf blight (MLB) over the past ten years necessitates rigorous identification and characterization of MLB-causing pathogens from different maize production zones to ensure the success of resistance breeding programs and the selection of appropriate disease management strategies. Although Bipolaris maydis is the primary pathogen causing MLB in India, other related genera such as Curvularia, Drechslera, and Exserohilum, and a taxonomically distant genus, Alternaria, are known to infect maize in other countries. To investigate the diversity of pathogens associated with MLB in India, 350 symptomatic leaf samples were collected between 2016 and 2018, from 20 MLB hotspots in nine states representing six ecological zones where maize is grown in India. Twenty representative fungal isolates causing MLB symptoms were characterized based on cultural, pathogenic, and molecular variability. Internal Transcribed Spacer (ITS) and glyceraldehyde-3-phosphate dehydrogenase (GADPH) gene sequence-based phylogenies showed that the majority of isolates (13/20) were Bipolaris maydis. There were also two Curvularia papendorfii isolates, and one isolate each of Bipolaris zeicola, Curvularia siddiquii, Curvularia sporobolicola, an unknown Curvularia sp. isolate phylogenetically close to C. graminicola, and an Alternaria sp. isolate. The B. zeicola, the aforesaid four Curvularia species, and the Alternaria sp. are the first reports of these fungi causing MLB in India. Pathogenicity tests on maize plants showed that isolates identified as Curvularia spp. and Alternaria sp. generally caused more severe MLB symptoms than those identified as Bipolaris spp. The diversity of fungi causing MLB, types of lesions, and variation in disease severity by different isolates described in this study provide baseline information for further investigations on MLB disease distribution, diagnosis, and management in India.

Abstract Background The biological control agent Aspergillus aculeatus Asp-4 colonizes and degrades sclerotia of Sclerotinia sclerotiorum resulting in reduced germination and disease caused by this important plant pathogen. Molecular mechanisms of mycoparasites underlying colonization, degradation, and reduction of germination of sclerotia of this and other important plant pathogens remain poorly understood. Results An RNA-Seq screen of Asp-4 growing on autoclaved, ground sclerotia of S. sclerotiorum for 48 h identified 997 up-regulated and 777 down-regulated genes relative to this mycoparasite growing on potato dextrose agar (PDA) for 48 h. qRT-PCR time course experiments characterized expression dynamics of select genes encoding enzymes functioning in degradation of sclerotial components and management of environmental conditions, including environmental stress. This analysis suggested co-temporal up-regulation of genes functioning in these two processes. Proteomic analysis of Asp-4 growing on this sclerotial material for 48 h identified 26 up-regulated and 6 down-regulated proteins relative to the PDA control. Certain proteins with increased abundance had putative functions in degradation of polymeric components of sclerotia and the mitigation of environmental stress. Conclusions Our results suggest co-temporal up-regulation of genes involved in degradation of sclerotial compounds and mitigation of environmental stress. This study furthers the analysis of mycoparasitism of sclerotial pathogens by providing the basis for molecular characterization of a previously uncharacterized mycoparasite-sclerotial interaction.

There is a pressing need for redesigning agriculture to achieve sustainability and for utilizing modern genetic tools, including genetic engineering, to add nutritional value to crops for the benefit of the diverse human population. Collectively, plant foods contain most minerals, macronutrients (calories), and micronutrients essential for human nutrition. These plant foods also contain a range of bioactive compounds that can play important roles in the prevention of chronic diseases including heart disease, cancer, stroke, diabetes, Alzheimer's, cataracts, and age-related functional decline. However, these bioactive nutrients are often present at marginal concentrations in edible plant tissues in regard to human nutrition/prevention of disease. The quantity of these nutrients in edible plant tissues is primarily dependent on crop genetics and regulated by complex and overlapping mechanisms in response to developmental and environmental cues. Environmental cues are naturally occurring—temperature, light intensity, and other stressors, or result from crop production system components—fertilizer, tillage operations, etc. One strategy for sustainable, next-generation crop development is to design cropping systems that have minimal or lesser impact on the environment and to use genetic approaches to enhance crop nutritional content. This strategy is appealing since crop genetics is the primary driver of plant nutrient content and because purely managing crop production fields to optimize crop nutrient content is extremely challenging if not impossible. As an example we present the development of a next-generation sustainable tomato production system with beneficial impacts on tomato physiology and nutritional quality of the tomato fruit. Our analysis of the metabolomes of tomato cultivars in this and other cropping systems highlights the need for robust cultivars that consistently express nutritional and other desirable traits across cropping systems and under differing environmental conditions.

As semiautonomous driving systems are becoming prevalent in late model vehicles, it is important to understand how such systems affect driver attention. This study investigated whether measures from low-cost devices monitoring peripheral physiological state were comparable to standard EEG in predicting lapses in attention to system failures. Twenty-five participants were equipped with a low-fidelity eye-tracker and heart rate monitor and with a high-fidelity NuAmps 32-channel quick-gel EEG system and asked to detect the presence of potential system failure while engaged in a fully autonomous lane changing driving task. To encourage participant attention to the road and to assess engagement in the lane changing task, participants were required to: (a) answer questions about that task; and (b) keep a running count of the type and number of billboards presented throughout the driving task. Linear mixed effects analyses were conducted to model the latency of responses reaction time (RT) to automation signals using the physiological metrics and time period. Alpha-band activity at the midline parietal region in conjunction with heart rate variability (HRV) was important in modeling RT over time. Results suggest that current low-fidelity technologies are not sensitive enough by themselves to reliably model RT to critical signals. However, that HRV interacted with EEG to significantly model RT points to the importance of further developing heart rate metrics for use in environments where it is not practical to use EEG.

Plant–soil microbe interactions are complex and affected by many factors including soil type, edaphic conditions, plant genotype and phenotype, and developmental stage. The rice rhizosphere microbial community composition of nine recombinant inbred lines (RILs) and their parents, Francis and Rondo, segregating for root and shoot biomass, was determined using metagenomic sequencing as a means to examine how biomass phenotype influences the rhizosphere community. Two plant developmental stages were studied, heading and physiological maturity, based on root and shoot biomass growth patterns across the selected genotypes. We used partial least squares (PLS) regression analysis to examine plant trait-driven microbial populations and identify microbial species, functions, and genes corresponding to root and shoot biomass as well as developmental stage patterns. Species identified correlated with increases in either root or shoot biomass were widely present in soil and included species involved in nitrogen cycling (Anaeromyxobacter spp.) and methane production (Methanocellaavoryzae), as well as known endophytes (Bradyrhizobium spp.). Additionally, PLS analysis allowed us to explore the relationship of developmental stage with species, microbial functions, and genes. Many of the community functions and genes observed during the heading stage were representative of cell growth (e.g., carbohydrate and nitrogen metabolism), while functions correlated with physiological maturity were indicative of cell decay. These results are consistent with the hypothesis that microbial communities exist whose metabolic and gene functions correspond to plant biomass traits.

The root nodules are a unique environment formed on legume roots through a highly specific symbiotic relationship between leguminous plants and nodule-inducing bacteria. Previously, Rhizobia were presumed to be the only group of bacteria residing within nodules. However, recent studies discovered diverse groups of bacteria within the legume nodules. In this report soybean nodule-associated bacteria were studied in an effort to identify beneficial bacteria for plant disease control and growth promotion. Analysis of surface-sterilized single nodules showed bacterial diversity of the nodule microbiome. Five hundred non-rhizobial colonies from 10 nodules, 50 colonies per nodule, were tested individually against the tomato wilt causing bacterial pathogen Clavibacter michiganensis subsp. michiganensis (Cmm) for inhibition of pathogen growth. From the initial screening, 54 isolates were selected based on significant growth inhibition of Cmm. These isolates were further tested in vitro on another bacterial pathogen Pseudomonas syringae pv. tomato (Pst) and two fungal pathogens Rhizoctonia solani and Sclerotinia sclerotiorum. Bacterial metabolites were extracted from 15 selected isolates with ethanol and tested against pathogen Cmm and Pst. These isolates were identified by using MALDI-TOF mass spectrometry and 16S rRNA gene sequencing. Pseudomonas spp. were the dominant soybean nodule-associated non-rhizobial bacterial group. Several isolates imparted significant protection against pathogens and/or plant growth promotion on tomato seedlings. The most promising nodule-associated bacterial isolate that suppressed both Cmm and Pst in vitro and Pst in tomato seedlings was identified as a Proteus species. Isolation and identification of beneficial nodule-associated bacteria established the foundation for further exploration of potential nodule-associated bacteria for plant protection and growth promotion.